{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## These are code samples for the following blog post: [Seaborn by Example: Data Visualization and Plotting using Python](http://queirozf.com/entries/seaborn-by-example-data-visualization-and-plotting-using-python)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) Just plot some 1D data using distplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5ec835ccf8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NpMosasnNcm+9FQr9T36idnmp2ZIlr3D99Y3brtKhQ1vGjz+HZ58N68z++teN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ec2d2aba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.normal(size=100)\n",
    "\n",
    "sns.distplot(x)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Global TF Kernel (Python 3)",
   "language": "python",
   "name": "global-tf-python-3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
